A Li-ion battery charge protocol with optimal aging-quality of service trade-off

The reduction of usable capacity of rechargeable batteries can be mitigated during the charge process by acting on some stress factors, namely, the average state-of-charge (SOC) and the charge current. Larger values of these quantities cause an increased degradation of battery capacity, so it would be desirable to keep both as low as possible, which is obviously in contrast with the objective of a fast charge. However, by exploiting the fact that in most battery-powered systems the time during which it is plugged for charging largely exceeds the time required to charge, it is possible to devise appropriate charge protocols that achieve a good balance between fast charge and aging. In this paper we propose a charge protocol that, using an accurate estimate of the charging time of a battery and the statistical properties of the charge/discharge patterns, yields an optimal trade-off between aging and quality of service. The latter is measured in terms of the distance of the actual SOC from 100% at the end of the charge phase. Results show that the present method improves significantly over other similar protocols proposed in the literature

A Li-ion battery charge protocol with optimal aging-quality of service trade-off

The reduction of usable capacity of rechargeable batteries can be mitigated during the charge process by acting on some stress factors, namely, the average state-of-charge (SOC) and the charge current. Larger values of these quantities cause an increased degradation of battery capacity, so it would be desirable to keep both as low as possible, which is obviously in contrast with the objective of a fast charge. However, by exploiting the fact that in most battery-powered systems the time during which it is plugged for charging largely exceeds the time required to charge, it is possible to devise appropriate charge protocols that achieve a good balance between fast charge and aging. In this paper we propose a charge protocol that, using an accurate estimate of the charging time of a battery and the statistical properties of the charge/discharge patterns, yields an optimal trade-off between aging and quality of service. The latter is measured in terms of the distance of the actual SOC from 100% at the end of the charge phase. Results show that the present method improves significantly over other similar protocols proposed in the literature

Electric Vehicles Plug-In Duration Forecasting Using Machine Learning for Battery Optimization

The aging of rechargeable batteries, with its associated replacement costs, is one of the main issues limiting the diffusion of electric vehicles (EVs) as the future transportation infrastructure. An effective way to mitigate battery aging is to act on its charge cycles, more controllable than discharge ones, implementing so-called battery-aware charging protocols. Since one of the main factors affecting battery aging is its average state of charge (SOC), these protocols try to minimize the standby time, i.e., the time interval between the end of the actual charge and the moment when the EV is unplugged from the charging station. Doing so while still ensuring that the EV is fully charged when needed (in order to achieve a satisfying user experience) requires a “just-in-time” charging protocol, which completes exactly at the plug-out time. This type of protocol can only be achieved if an estimate of the expected plug-in duration is available. While many previous works have stressed the importance of having this estimate, they have either used straightforward forecasting methods, or assumed that the plug-in duration was directly indicated by the user, which could lead to sub-optimal results. In this paper, we evaluate the effectiveness of a more advanced forecasting based on machine learning (ML). With experiments on a public dataset containing data from domestic EV charge points, we show that a simple tree-based ML model, trained on each charge station based on its users’ behaviour, can reduce the forecasting error by up to 4× compared to the simple predictors used in previous works. This, in turn, leads to an improvement of up to 50% in a combined aging-quality of service metric

Effect of in-hospital comprehensive geriatric assessment (CGA) in older people with hip fracture : the protocol of the Trondheim Hip Fracture Trial

Background: Hip fractures in older people are associated with high morbidity, mortality, disability and reduction in quality of life. Traditionally people with hip fracture are cared for in orthopaedic departments without additional geriatric assessment. However, studies of postoperative rehabilitation indicate improved efficiency of multidisciplinary geriatric rehabilitation as compared to traditional care. This randomized controlled trial (RCT) aims to investigate whether an additional comprehensive geriatric assessment of hip fracture patients in a special orthogeriatric unit during the acute in-hospital phase may improve outcomes as compared to treatment as usual in an orthopaedic unit. Methods/design: The intervention of interest, a comprehensive geriatric assessment is compared with traditional care in an orthopaedic ward. The study includes 401 home-dwelling older persons >70 years of age, previously able to walk 10 meters and now treated for hip fracture at St. Olav Hospital, Trondheim, Norway. The participants are enrolled and randomised during the stay in the Emergency Department. Primary outcome measure is mobility measured by the Short Physical Performance Battery (SPPB) at 4 months after surgery. Secondary outcomes measured at 1, 4 and 12 months postoperatively are place of residence, activities of daily living, balance and gait, falls and fear of falling, quality of life and depressive symptoms, as well as use of health care resources and survival. Discussion: We believe that the design of the study, the randomisation procedure and outcome measurements will be of sufficient strength and quality to evaluate the impact of comprehensive geriatric assessment on mobility and other relevant outcomes in hip fracture patients

A 3D Framework for Characterizing Microstructure Evolution of Li-Ion Batteries

Lithium-ion batteries are commonly found in many modern consumer devices, ranging from portable computers and mobile phones to hybrid- and fully-electric vehicles. While improving efficiencies and increasing reliabilities are of critical importance for increasing market adoption of the technology, research on these topics is, to date, largely restricted to empirical observations and computational simulations. In the present study, it is proposed to use the modern technique of X-ray microscopy to characterize a sample of commercial 18650 cylindrical Li-ion batteries in both their pristine and aged states. By coupling this approach with 3D and 4D data analysis techniques, the present study aimed to create a research framework for characterizing the microstructure evolution leading to capacity fade in a commercial battery. The results indicated the unique capabilities of the microscopy technique to observe the evolution of these batteries under aging conditions, successfully developing a workflow for future research studies

Monitoring and Fault Location Sensor Network for Underground Distribution Lines

One of the fundamental tasks of electric distribution utilities is guaranteeing a continuous supply of electricity to their customers. The primary distribution network is a critical part of these facilities because a fault in it could affect thousands of customers. However, the complexity of this network has been increased with the irruption of distributed generation, typical in a Smart Grid and which has significantly complicated some of the analyses, making it impossible to apply traditional techniques. This problem is intensified in underground lines where access is limited. As a possible solution, this paper proposes to make a deployment of a distributed sensor network along the power lines. This network proposes taking advantage of its distributed character to support new approaches of these analyses. In this sense, this paper describes the aquiculture of the proposed network (adapted to the power grid) based on nodes that use power line communication and energy harvesting techniques. In this sense, it also describes the implementation of a real prototype that has been used in some experiments to validate this technological adaptation. Additionally, beyond a simple use for monitoring, this paper also proposes the use of this approach to solve two typical distribution system operator problems, such as: fault location and failure forecasting in power cables.Ministerio de Economía y Competitividad, Government of Spain project Sistema Inteligente Inalámbrico para Análisis y Monitorización de Líneas de Tensión Subterráneas en Smart Grids (SIIAM) TEC2013-40767-RMinisterio de Educación, Cultura y Deporte, Government of Spain, for the funding of the scholarship Formación de Profesorado Universitario 2016 (FPU 2016

Physical activity intervention for elderly patients with reduced physical performance after acute coronary syndrome (HULK study): Rationale and design of a randomized clinical trial

Background: Reduced physical performance and impaired mobility are common in elderly patients after acute coronary syndrome (ACS) and they represent independent risk factors for disability, morbidity, hospital readmission and mortality. Regular physical exercise represents a means for improving functional capacity. Nevertheless, its clinical benefit has been less investigated in elderly patients in the early phase after ACS. The HULK trial aims to investigate the clinical benefit of an early, tailored low-cost physical activity intervention in comparison to standard of care in elderly ACS patients with reduced physical performance. Design: HULK is an investigator-initiated, prospective multicenter randomized controlled trial (NCT03021044). After successful management of the ACS acute phase and uneventful first 1 month, elderly (≥70 years) patients showing reduced physical performance are randomized (1:1 ratio) to either standard of care or physical activity intervention. Reduced physical performance is defined as a short physical performance battery (SPPB) score of 4-9. The early, tailored, low-cost physical intervention includes 4 sessions of physical activity with a supervisor and an home-based program of physical exercise. The chosen primary endpoint is the 6-month SPPB value. Secondary endpoints briefly include quality of life, on-treatment platelet reactivity, some laboratory data and clinical adverse events. To demonstrate an increase of at least one SPPB point in the experimental arm, a sample size of 226 patients is needed. Conclusions: The HULK study will test the hypothesis that an early, tailored low-cost physical activity intervention improves physical performance, quality of life, frailty status and outcome in elderly ACS patients with reduced physical performance

ITERL: A Wireless Adaptive System for Efficient Road Lighting

This work presents the development and construction of an adaptive street lighting system that improves safety at intersections, which is the result of applying low-power Internet of Things (IoT) techniques to intelligent transportation systems. A set of wireless sensor nodes using the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard with additional internet protocol (IP) connectivity measures both ambient conditions and vehicle transit. These measurements are sent to a coordinator node that collects and passes them to a local controller, which then makes decisions leading to the streetlight being turned on and its illumination level controlled. Streetlights are autonomous, powered by photovoltaic energy, and wirelessly connected, achieving a high degree of energy efficiency. Relevant data are also sent to the highway conservation center, allowing it to maintain up-to-date information for the system, enabling preventive maintenance.Consejería de Fomento y Vivienda Junta de Andalucía G-GI3002 / IDIOFondo Europeo de Desarrollo Regional G-GI3002 / IDI

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits